Comprehensive algorithm for quantitative real-time polymerase chain reaction
Comprehensive algorithm for quantitative real-time polymerase chain reaction
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DOI：
10.1089/cmb.2005.12.1047
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发表时间：
2005-10-01
影响因子：
1.7
通讯作者：
Fernald, RD
中科院分区：
文献类型：
--
作者：
Zhao, S;Fernald, RD
定量实时聚合酶链式反应(qRT-PCR)已成为快速、灵敏、定量比较RNA转录本丰度的首选方法。来自这种方法的有用数据依赖于将数据与允许计算mRNA水平的理论曲线进行拟合。计算准确的mRNA水平需要使用重要的参数，如反应效率和阈值下的循环分数(CT)；然而，目前使用的许多算法都估计这些重要参数。在这里，我们描述了一种客观的方法，利用基于单个PCR反应的动力学的计算来量化qRT-PCR结果，而不需要标准曲线，独立于允许直接计算效率和CT的任何假设或主观判断。我们使用四参数Logistic模型来拟合原始荧光数据作为聚合酶链式反应周期的函数，以确定反应的指数阶段。接下来，我们使用一个三参数的简单指数模型来拟合指数阶段，并使用迭代的非线性回归算法。在曲线的指数部分，我们的技术使用回归的P值自动识别候选回归值，然后使用加权平均来计算最终的量化效率。对于CT的测定，我们从Logistic模型中选取第一个正的二阶导数最大值。该算法提供了一种客观和抗噪声的方法，用于定量qRT-PCR结果，该方法独立于用于执行PCR反应的特定设备。
Quantitative real-time polymerase chain reactions (qRT-PCR) have become the method of choice for rapid, sensitive, quantitative comparison of RNA transcript abundance. Useful data from this method depend on fitting data to theoretical curves that allow computation of mRNA levels. Calculating accurate mRNA levels requires important parameters such as reaction efficiency and the fractional cycle number at threshold (CT) to be used; however, many algorithms currently in use estimate these important parameters. Here we describe an objective method for quantifying qRT-PCR results using calculations based on the kinetics of individual PCR reactions without the need of the standard curve, independent of any assumptions or subjective judgments which allow direct calculation of efficiency and CT. We use a four-parameter logistic model to fit the raw fluorescence data as a function of PCR cycles to identify the exponential phase of the reaction. Next, we use a three-parameter simple exponent model to fit the exponential phase using an iterative nonlinear regression algorithm. Within the exponential portion of the curve, our technique automatically identifies candidate regression values using the P-value of regression and then uses a weighted average to compute a final efficiency for quantification. For CT determination, we chose the first positive second derivative maximum from the logistic model. This algorithm provides an objective and noise-resistant method for quantification of qRT-PCR results that is independent of the specific equipment used to perform PCR reactions.